Kruskal-Wallis test, or the nonparametric version of the ANOVA {https://t.co/J0W0co9lrX} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
Visualizing economic data with pretty worldmaps {https://t.co/A3CfPt4p3u} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
Learning about data structures in R {https://t.co/munnPpDiwl} #rstats #DataScience
— R-bloggers (@Rbloggers) March 23, 2022
R Shiny in Life Sciences – Top 7 Dashboard Examples {https://t.co/iNZgHjyP7K} #rstats #DataScience
— R-bloggers (@Rbloggers) March 29, 2022
Simulating time-to-event outcomes with non-proportional hazards {https://t.co/uNHyjLyFVH} #rstats #DataScience
— R-bloggers (@Rbloggers) March 29, 2022
Wide To Long Form data in R {https://t.co/YVq347TdDM} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
How to use functional programming for ggplot {https://t.co/G0oOUeWXlX} #rstats #DataScience
— R-bloggers (@Rbloggers) March 25, 2022
How to Use https://t.co/oxocLwo2Hu in R with examples {https://t.co/HguhnjtShW} #rstats #DataScience
— R-bloggers (@Rbloggers) March 23, 2022
February 2022: “Top 40” New CRAN Packages {https://t.co/2DtXwp7qDj} #rstats #DataScience
— R-bloggers (@Rbloggers) March 28, 2022
Creating APIs for Data Science With plumber {https://t.co/XzUQSn7UB5} #rstats #DataScience
— R-bloggers (@Rbloggers) March 23, 2022
Searching and browsing the R universe {https://t.co/6zPZQJFNfz} #rstats #DataScience
— R-bloggers (@Rbloggers) March 23, 2022
Batched Imputation for High Dimensional Missing Data Problems {https://t.co/8nhem6CymH} #rstats #DataScience
— R-bloggers (@Rbloggers) March 24, 2022
Complete tutorial on using ‘apply’ functions in R {https://t.co/gAI41Kqk2l} #rstats #DataScience
— R-bloggers (@Rbloggers) March 8, 2022
How to Get Twitter Data using R {https://t.co/lJrAu2tCKh} #rstats #DataScience
— R-bloggers (@Rbloggers) March 5, 2022
Monte Carlo Analysis in R {https://t.co/X5J5EgA3u4} #rstats #DataScience
— R-bloggers (@Rbloggers) March 12, 2022
Interaction Plot in R: How to Visualize Interaction Effect Between Variables {https://t.co/xukbymp89x} #rstats #DataScience
— R-bloggers (@Rbloggers) March 1, 2022
Markov Chain Introduction in R {https://t.co/M4iyIbjj62} #rstats #DataScience
— R-bloggers (@Rbloggers) March 13, 2022
How to use pipes to clean up your R code {https://t.co/4XPpXS2SMl} #rstats #DataScience
— R-bloggers (@Rbloggers) March 2, 2022
How to Use R and Python Together? Try These 2 Packages {https://t.co/bBnt7pG52N} #rstats #DataScience
— R-bloggers (@Rbloggers) March 22, 2022
Dual axis charts – how to make them and why they can be useful {https://t.co/xxw2uwEMvo} #rstats #DataScience
— R-bloggers (@Rbloggers) March 14, 2022
Predictive Analytics Models in R {https://t.co/XlkJAaLryA} #rstats #DataScience
— R-bloggers (@Rbloggers) March 13, 2022
Understanding the native R pipe |> {https://t.co/rOPUrHbmtR} #rstats #DataScience
— R-bloggers (@Rbloggers) March 15, 2022
Why RStudio Supports Python for Data Science {https://t.co/Tr51fN6ipJ} #rstats #DataScience
— R-bloggers (@Rbloggers) March 2, 2022
Dashboards in R Shiny {https://t.co/BbirS9zEnj} #rstats #DataScience
— R-bloggers (@Rbloggers) March 15, 2022
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```